Overview

Dataset statistics

Number of variables27
Number of observations5840
Missing cells0
Missing cells (%)0.0%
Duplicate rows4
Duplicate rows (%)0.1%
Total size in memory513.4 KiB
Average record size in memory90.0 B

Variable types

Numeric9
Boolean18

Alerts

Dataset has 4 (0.1%) duplicate rowsDuplicates
fuel_Diesel is highly overall correlated with fuel_Petrol and 1 other fieldsHigh correlation
fuel_Petrol is highly overall correlated with fuel_Diesel and 1 other fieldsHigh correlation
km_driven is highly overall correlated with km_driven_squared and 2 other fieldsHigh correlation
km_driven_squared is highly overall correlated with km_driven and 2 other fieldsHigh correlation
max_power is highly overall correlated with name and 3 other fieldsHigh correlation
max_torque_rpm is highly overall correlated with fuel_Diesel and 2 other fieldsHigh correlation
mileage is highly overall correlated with seats_5High correlation
name is highly overall correlated with max_power and 3 other fieldsHigh correlation
seats_4 is highly overall correlated with max_powerHigh correlation
seats_5 is highly overall correlated with mileage and 1 other fieldsHigh correlation
seats_7 is highly overall correlated with seats_5High correlation
torque is highly overall correlated with max_power and 2 other fieldsHigh correlation
transmission_Manual is highly overall correlated with max_powerHigh correlation
year is highly overall correlated with km_driven and 3 other fieldsHigh correlation
year_squared is highly overall correlated with km_driven and 3 other fieldsHigh correlation
fuel_LPG is highly imbalanced (94.8%)Imbalance
seller_type_Individual is highly imbalanced (51.3%)Imbalance
seller_type_Trustmark Dealer is highly imbalanced (96.0%)Imbalance
transmission_Manual is highly imbalanced (57.6%)Imbalance
owner_Fourth & Above Owner is highly imbalanced (83.7%)Imbalance
owner_Test Drive Car is highly imbalanced (99.2%)Imbalance
owner_Third Owner is highly imbalanced (60.6%)Imbalance
seats_4 is highly imbalanced (88.1%)Imbalance
seats_6 is highly imbalanced (93.1%)Imbalance
seats_8 is highly imbalanced (79.2%)Imbalance
seats_9 is highly imbalanced (90.8%)Imbalance
seats_10 is highly imbalanced (97.0%)Imbalance
seats_14 is highly imbalanced (99.8%)Imbalance
km_driven_squared is highly skewed (γ1 = 62.45997268)Skewed

Reproduction

Analysis started2025-12-04 01:02:06.586846
Analysis finished2025-12-04 01:02:11.444273
Duration4.86 seconds
Software versionydata-profiling vv4.18.0
Download configurationconfig.json

Variables

mileage
Real number (ℝ)

High correlation 

Distinct376
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.430841
Minimum0
Maximum42
Zeros14
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2025-12-04T04:02:11.488770image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12.8285
Q116.95
median19.37
Q322.3
95-th percentile25.8
Maximum42
Range42
Interquartile range (IQR)5.35

Descriptive statistics

Standard deviation3.9859732
Coefficient of variation (CV)0.20513642
Kurtosis0.87209172
Mean19.430841
Median Absolute Deviation (MAD)2.63
Skewness-0.17505703
Sum113476.11
Variance15.887982
MonotonicityNot monotonic
2025-12-04T04:02:11.553299image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.37186
 
3.2%
18.9175
 
3.0%
19.7137
 
2.3%
18.6126
 
2.2%
21.1118
 
2.0%
17105
 
1.8%
15.9695
 
1.6%
17.890
 
1.5%
16.184
 
1.4%
15.176
 
1.3%
Other values (366)4648
79.6%
ValueCountFrequency (%)
014
0.2%
94
 
0.1%
9.51
 
< 0.1%
102
 
< 0.1%
10.12
 
< 0.1%
10.514
0.2%
10.711
 
< 0.1%
10.751
 
< 0.1%
10.81
 
< 0.1%
10.94
 
0.1%
ValueCountFrequency (%)
421
 
< 0.1%
33.442
 
< 0.1%
331
 
< 0.1%
32.521
 
< 0.1%
30.462
 
< 0.1%
28.470
1.2%
28.0929
0.5%
27.625
 
0.1%
27.44
 
0.1%
27.3920
 
0.3%

max_power
Real number (ℝ)

High correlation 

Distinct313
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.892354
Minimum0
Maximum400
Zeros4
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2025-12-04T04:02:11.600181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile47.3
Q168
median81.86
Q399
95-th percentile147.9
Maximum400
Range400
Interquartile range (IQR)31

Descriptive statistics

Standard deviation31.661223
Coefficient of variation (CV)0.36022728
Kurtosis6.0363004
Mean87.892354
Median Absolute Deviation (MAD)14.81
Skewness1.793812
Sum513291.35
Variance1002.433
MonotonicityNot monotonic
2025-12-04T04:02:11.647855image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
81.86287
 
4.9%
74260
 
4.5%
88.5163
 
2.8%
67130
 
2.2%
46.3127
 
2.2%
67.1117
 
2.0%
62.1116
 
2.0%
81.8115
 
2.0%
67.04115
 
2.0%
70110
 
1.9%
Other values (303)4300
73.6%
ValueCountFrequency (%)
04
 
0.1%
32.82
 
< 0.1%
34.217
 
0.3%
3514
 
0.2%
35.52
 
< 0.1%
3769
1.2%
37.487
 
0.1%
37.56
 
0.1%
381
 
< 0.1%
38.42
 
< 0.1%
ValueCountFrequency (%)
4001
 
< 0.1%
2821
 
< 0.1%
2801
 
< 0.1%
2721
 
< 0.1%
270.93
0.1%
2651
 
< 0.1%
261.44
0.1%
2582
< 0.1%
254.83
0.1%
254.791
 
< 0.1%

torque
Real number (ℝ)

High correlation 

Distinct240
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean175.36266
Minimum47.088
Maximum1863.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2025-12-04T04:02:11.696013image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum47.088
5-th percentile69
Q1111.8
median160
Q3200.124
95-th percentile330
Maximum1863.9
Range1816.812
Interquartile range (IQR)88.324

Descriptive statistics

Standard deviation107.16174
Coefficient of variation (CV)0.6110864
Kurtosis50.367813
Mean175.36266
Median Absolute Deviation (MAD)47
Skewness4.9916845
Sum1024118
Variance11483.638
MonotonicityNot monotonic
2025-12-04T04:02:11.744312image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
200503
 
8.6%
190454
 
7.8%
160326
 
5.6%
90297
 
5.1%
114191
 
3.3%
113148
 
2.5%
62130
 
2.2%
250110
 
1.9%
330101
 
1.7%
69101
 
1.7%
Other values (230)3479
59.6%
ValueCountFrequency (%)
47.0881
 
< 0.1%
481
 
< 0.1%
5113
 
0.2%
55.9171
 
< 0.1%
572
 
< 0.1%
58.861
 
< 0.1%
5985
1.5%
59.84112
 
0.2%
602
 
< 0.1%
62130
2.2%
ValueCountFrequency (%)
1863.91
 
< 0.1%
1422.459
0.2%
1275.33
 
0.1%
1128.155
0.1%
1079.11
 
< 0.1%
7893
 
0.1%
6401
 
< 0.1%
6206
0.1%
6193
 
0.1%
6003
 
0.1%

max_torque_rpm
Real number (ℝ)

High correlation 

Distinct46
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3045.789
Minimum1400
Maximum21800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2025-12-04T04:02:11.789974image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1400
5-th percentile1750
Q12250
median3000
Q34000
95-th percentile4500
Maximum21800
Range20400
Interquartile range (IQR)1750

Descriptive statistics

Standard deviation911.03932
Coefficient of variation (CV)0.29911439
Kurtosis29.477441
Mean3045.789
Median Absolute Deviation (MAD)750
Skewness1.6483615
Sum17787408
Variance829992.65
MonotonicityNot monotonic
2025-12-04T04:02:11.839978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
4000738
12.6%
3000686
11.7%
2000657
11.2%
3500566
9.7%
2500457
 
7.8%
1750430
 
7.4%
2750349
 
6.0%
2800313
 
5.4%
4200191
 
3.3%
4500182
 
3.1%
Other values (36)1271
21.8%
ValueCountFrequency (%)
14002
 
< 0.1%
150064
 
1.1%
16001
 
< 0.1%
17401
 
< 0.1%
1750430
7.4%
180038
 
0.7%
18501
 
< 0.1%
190044
 
0.8%
2000657
11.2%
2200140
 
2.4%
ValueCountFrequency (%)
218001
 
< 0.1%
53001
 
< 0.1%
52001
 
< 0.1%
500022
 
0.4%
485018
 
0.3%
480075
1.3%
47507
 
0.1%
47008
 
0.1%
460051
 
0.9%
4500182
3.1%

name
Real number (ℝ)

High correlation 

Distinct2933
Distinct (%)50.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean499400.64
Minimum30000
Maximum6373000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2025-12-04T04:02:11.887563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum30000
5-th percentile124349.87
Q1273749.94
median479924.2
Q3574113.64
95-th percentile1000000
Maximum6373000
Range6343000
Interquartile range (IQR)300363.69

Descriptive statistics

Standard deviation422914.85
Coefficient of variation (CV)0.84684483
Kurtosis65.19333
Mean499400.64
Median Absolute Deviation (MAD)160000
Skewness6.2761005
Sum2.9164997 × 109
Variance1.7885697 × 1011
MonotonicityNot monotonic
2025-12-04T04:02:11.936182image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
522960.0911912
 
15.6%
20000034
 
0.6%
50000033
 
0.6%
35000033
 
0.6%
40000031
 
0.5%
70000030
 
0.5%
25000029
 
0.5%
30000028
 
0.5%
60000027
 
0.5%
65000027
 
0.5%
Other values (2923)4656
79.7%
ValueCountFrequency (%)
300001
 
< 0.1%
350001
 
< 0.1%
400001
 
< 0.1%
420001
 
< 0.1%
450003
0.1%
462501
 
< 0.1%
487501
 
< 0.1%
500001
 
< 0.1%
50500.307691
 
< 0.1%
525002
< 0.1%
ValueCountFrequency (%)
63730001
< 0.1%
62230001
< 0.1%
60730001
< 0.1%
60000001
< 0.1%
5943333.3331
< 0.1%
58500001
< 0.1%
5833333.3331
< 0.1%
58000001
< 0.1%
5776666.6672
< 0.1%
56500002
< 0.1%

fuel_Diesel
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
True
3177 
False
2663 
ValueCountFrequency (%)
True3177
54.4%
False2663
45.6%
2025-12-04T04:02:11.965500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

fuel_LPG
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
5806 
True
 
34
ValueCountFrequency (%)
False5806
99.4%
True34
 
0.6%
2025-12-04T04:02:11.983314image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

fuel_Petrol
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
3261 
True
2579 
ValueCountFrequency (%)
False3261
55.8%
True2579
44.2%
2025-12-04T04:02:11.999794image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

seller_type_Individual
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
True
5223 
False
617 
ValueCountFrequency (%)
True5223
89.4%
False617
 
10.6%
2025-12-04T04:02:12.017936image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

seller_type_Trustmark Dealer
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
5815 
True
 
25
ValueCountFrequency (%)
False5815
99.6%
True25
 
0.4%
2025-12-04T04:02:12.150941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

transmission_Manual
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
True
5336 
False
 
504
ValueCountFrequency (%)
True5336
91.4%
False504
 
8.6%
2025-12-04T04:02:12.167551image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

owner_Fourth & Above Owner
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
5700 
True
 
140
ValueCountFrequency (%)
False5700
97.6%
True140
 
2.4%
2025-12-04T04:02:12.184683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
4201 
True
1639 
ValueCountFrequency (%)
False4201
71.9%
True1639
 
28.1%
2025-12-04T04:02:12.201648image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

owner_Test Drive Car
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
5836 
True
 
4
ValueCountFrequency (%)
False5836
99.9%
True4
 
0.1%
2025-12-04T04:02:12.218267image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

owner_Third Owner
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
5386 
True
 
454
ValueCountFrequency (%)
False5386
92.2%
True454
 
7.8%
2025-12-04T04:02:12.234163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

seats_4
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
5746 
True
 
94
ValueCountFrequency (%)
False5746
98.4%
True94
 
1.6%
2025-12-04T04:02:12.250698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

seats_5
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
True
4618 
False
1222 
ValueCountFrequency (%)
True4618
79.1%
False1222
 
20.9%
2025-12-04T04:02:12.266757image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

seats_6
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
5792 
True
 
48
ValueCountFrequency (%)
False5792
99.2%
True48
 
0.8%
2025-12-04T04:02:12.284019image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

seats_7
Boolean

High correlation 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
5040 
True
800 
ValueCountFrequency (%)
False5040
86.3%
True800
 
13.7%
2025-12-04T04:02:12.300400image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

seats_8
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
5649 
True
 
191
ValueCountFrequency (%)
False5649
96.7%
True191
 
3.3%
2025-12-04T04:02:12.317528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

seats_9
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
5772 
True
 
68
ValueCountFrequency (%)
False5772
98.8%
True68
 
1.2%
2025-12-04T04:02:12.333227image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

seats_10
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
5822 
True
 
18
ValueCountFrequency (%)
False5822
99.7%
True18
 
0.3%
2025-12-04T04:02:12.349127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

seats_14
Boolean

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size5.8 KiB
False
5839 
True
 
1
ValueCountFrequency (%)
False5839
> 99.9%
True1
 
< 0.1%
2025-12-04T04:02:12.364721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

year
Real number (ℝ)

High correlation 

Distinct29
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.4284
Minimum1983
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2025-12-04T04:02:12.390646image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1983
5-th percentile2006
Q12011
median2014
Q32017
95-th percentile2019
Maximum2020
Range37
Interquartile range (IQR)6

Descriptive statistics

Standard deviation4.0956219
Coefficient of variation (CV)0.0020341532
Kurtosis1.692979
Mean2013.4284
Median Absolute Deviation (MAD)3
Skewness-1.0194703
Sum11758422
Variance16.774119
MonotonicityNot monotonic
2025-12-04T04:02:12.430818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
2017666
11.4%
2016596
10.2%
2015568
9.7%
2018522
8.9%
2012507
8.7%
2014480
8.2%
2013478
8.2%
2011461
7.9%
2010322
 
5.5%
2019298
 
5.1%
Other values (19)942
16.1%
ValueCountFrequency (%)
19831
 
< 0.1%
19911
 
< 0.1%
19943
 
0.1%
19951
 
< 0.1%
19963
 
0.1%
199710
0.2%
19989
0.2%
199912
0.2%
200019
0.3%
20017
 
0.1%
ValueCountFrequency (%)
202058
 
1.0%
2019298
5.1%
2018522
8.9%
2017666
11.4%
2016596
10.2%
2015568
9.7%
2014480
8.2%
2013478
8.2%
2012507
8.7%
2011461
7.9%

km_driven
Real number (ℝ)

High correlation 

Distinct827
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73952.242
Minimum1
Maximum2360457
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2025-12-04T04:02:12.475674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11000
Q139000
median70000
Q3100000
95-th percentile156041
Maximum2360457
Range2360456
Interquartile range (IQR)61000

Descriptive statistics

Standard deviation60071.137
Coefficient of variation (CV)0.81229635
Kurtosis416.02464
Mean73952.242
Median Absolute Deviation (MAD)30000
Skewness12.645506
Sum4.318811 × 108
Variance3.6085414 × 109
MonotonicityNot monotonic
2025-12-04T04:02:12.556787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
120000429
 
7.3%
80000356
 
6.1%
70000350
 
6.0%
60000327
 
5.6%
50000305
 
5.2%
100000279
 
4.8%
90000262
 
4.5%
40000227
 
3.9%
110000225
 
3.9%
30000184
 
3.2%
Other values (817)2896
49.6%
ValueCountFrequency (%)
11
 
< 0.1%
10005
0.1%
13001
 
< 0.1%
13031
 
< 0.1%
15002
 
< 0.1%
16001
 
< 0.1%
16201
 
< 0.1%
20006
0.1%
21181
 
< 0.1%
21361
 
< 0.1%
ValueCountFrequency (%)
23604571
< 0.1%
15000001
< 0.1%
5774141
< 0.1%
5000002
< 0.1%
4750001
< 0.1%
4400001
< 0.1%
4260001
< 0.1%
3800001
< 0.1%
3764121
< 0.1%
3700001
< 0.1%

year_squared
Real number (ℝ)

High correlation 

Distinct29
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4053910.8
Minimum3932289
Maximum4080400
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2025-12-04T04:02:12.595353image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum3932289
5-th percentile4024036
Q14044121
median4056196
Q34068289
95-th percentile4076361
Maximum4080400
Range148111
Interquartile range (IQR)24168

Descriptive statistics

Standard deviation16475.411
Coefficient of variation (CV)0.0040640783
Kurtosis1.6549167
Mean4053910.8
Median Absolute Deviation (MAD)12075
Skewness-1.0113861
Sum2.3674839 × 1010
Variance2.7143917 × 108
MonotonicityNot monotonic
2025-12-04T04:02:12.635668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
4068289666
11.4%
4064256596
10.2%
4060225568
9.7%
4072324522
8.9%
4048144507
8.7%
4056196480
8.2%
4052169478
8.2%
4044121461
7.9%
4040100322
 
5.5%
4076361298
 
5.1%
Other values (19)942
16.1%
ValueCountFrequency (%)
39322891
 
< 0.1%
39640811
 
< 0.1%
39760363
 
0.1%
39800251
 
< 0.1%
39840163
 
0.1%
398800910
0.2%
39920049
0.2%
399600112
0.2%
400000019
0.3%
40040017
 
0.1%
ValueCountFrequency (%)
408040058
 
1.0%
4076361298
5.1%
4072324522
8.9%
4068289666
11.4%
4064256596
10.2%
4060225568
9.7%
4056196480
8.2%
4052169478
8.2%
4048144507
8.7%
4044121461
7.9%

km_driven_squared
Real number (ℝ)

High correlation  Skewed 

Distinct827
Distinct (%)14.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.0768577 × 109
Minimum1
Maximum5.5717572 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size45.8 KiB
2025-12-04T04:02:12.678930image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.21 × 108
Q11.521 × 109
median4.9 × 109
Q31 × 1010
95-th percentile2.4348794 × 1010
Maximum5.5717572 × 1012
Range5.5717572 × 1012
Interquartile range (IQR)8.479 × 109

Descriptive statistics

Standard deviation7.9544179 × 1010
Coefficient of variation (CV)8.7634049
Kurtosis4205.345
Mean9.0768577 × 109
Median Absolute Deviation (MAD)3.675 × 109
Skewness62.459973
Sum5.3008849 × 1013
Variance6.3272764 × 1021
MonotonicityNot monotonic
2025-12-04T04:02:12.725354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.44 × 1010429
 
7.3%
6400000000356
 
6.1%
4900000000350
 
6.0%
3600000000327
 
5.6%
2500000000305
 
5.2%
1 × 1010279
 
4.8%
8100000000262
 
4.5%
1600000000227
 
3.9%
1.21 × 1010225
 
3.9%
900000000184
 
3.2%
Other values (817)2896
49.6%
ValueCountFrequency (%)
11
 
< 0.1%
10000005
0.1%
16900001
 
< 0.1%
16978091
 
< 0.1%
22500002
 
< 0.1%
25600001
 
< 0.1%
26244001
 
< 0.1%
40000006
0.1%
44859241
 
< 0.1%
45624961
 
< 0.1%
ValueCountFrequency (%)
5.571757249 × 10121
< 0.1%
2.25 × 10121
< 0.1%
3.334069274 × 10111
< 0.1%
2.5 × 10112
< 0.1%
2.25625 × 10111
< 0.1%
1.936 × 10111
< 0.1%
1.81476 × 10111
< 0.1%
1.444 × 10111
< 0.1%
1.416859937 × 10111
< 0.1%
1.369 × 10111
< 0.1%

Interactions

2025-12-04T04:02:10.873371image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.362973image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.823874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.264979image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.624505image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.309925image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.667752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.043056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.393641image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.909793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.416207image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.863337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.303114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.663208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.346971image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.707401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.081774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.434531image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.949721image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.482208image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.905754image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.344473image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.707171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.388116image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.749804image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.121610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.478056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.989617image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.561539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.951265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.382978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.749327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.427707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.792115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.160697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.617455image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:11.030256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.639245image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.005458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.424874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.794204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.469431image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.836528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.203214image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.662584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:11.101709image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.672558image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.053610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.462745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.836850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.507474image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.878661image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.240497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.705300image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:11.143211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.711598image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.097291image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.504170image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.878640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.549123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.918874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.279992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.747743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:11.180838image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.746793image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.140869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.543781image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.225648image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.587517image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.959488image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.316019image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.787408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:11.222963image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:07.787416image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.225085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:08.584995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.269363image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:09.629006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.002038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.356326image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-04T04:02:10.831086image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-12-04T04:02:12.774911image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
fuel_Dieselfuel_LPGfuel_Petrolkm_drivenkm_driven_squaredmax_powermax_torque_rpmmileagenameowner_Fourth & Above Ownerowner_Second Ownerowner_Test Drive Carowner_Third Ownerseats_10seats_14seats_4seats_5seats_6seats_7seats_8seats_9seller_type_Individualseller_type_Trustmark Dealertorquetransmission_Manualyearyear_squared
fuel_Diesel1.0000.0800.9710.0690.0020.2570.8080.3340.2640.0000.0390.0180.0000.0460.0000.1160.3110.0100.3060.1140.0970.0220.0520.4020.0060.2000.200
fuel_LPG0.0801.0000.0640.0000.0000.0610.0400.0620.0000.0000.0070.0000.0000.0000.0000.0000.0340.0000.0240.0000.0000.0000.0000.0000.0140.1160.116
fuel_Petrol0.9710.0641.0000.0740.0030.2400.7990.3550.2520.0000.0440.0190.0000.0440.0000.1140.3010.0050.2960.1110.0940.0120.0540.3890.0190.1980.198
km_driven0.0690.0000.0741.0001.0000.041-0.321-0.198-0.1680.0510.0260.0000.0290.0100.0000.0000.1150.0000.0890.0820.0000.0220.0000.2430.016-0.570-0.570
km_driven_squared0.0020.0000.0031.0001.0000.041-0.321-0.198-0.1680.0000.0130.0000.0000.0000.0000.0000.0190.0000.0280.0000.0000.0000.0000.2430.000-0.570-0.570
max_power0.2570.0610.2400.0410.0411.000-0.025-0.3080.5880.0350.0620.1040.0440.0450.0000.7780.3480.0220.3270.1590.0480.2120.0480.7790.5130.1660.166
max_torque_rpm0.8080.0400.799-0.321-0.321-0.0251.000-0.177-0.1370.0320.0800.0290.0550.0390.0000.0530.2980.0000.2450.1000.0810.0000.067-0.5260.0510.0770.077
mileage0.3340.0620.355-0.198-0.198-0.308-0.1771.000-0.0150.0680.1050.0370.1000.1110.0600.2160.6000.1190.4370.2880.1880.0580.000-0.1620.2490.3460.346
name0.2640.0000.252-0.168-0.1680.588-0.137-0.0151.0000.0450.0910.4720.0760.0000.0000.1320.2560.0000.3090.0250.0000.1770.0210.5590.3480.5410.541
owner_Fourth & Above Owner0.0000.0000.0000.0510.0000.0350.0320.0680.0451.0000.0960.0000.0410.0000.0000.0260.0000.0000.0130.0210.0000.0500.0000.0000.0230.2220.222
owner_Second Owner0.0390.0070.0440.0260.0130.0620.0800.1050.0910.0961.0000.0000.1800.0000.0000.0280.0040.0000.0000.0140.0100.1130.0160.0220.0470.2970.297
owner_Test Drive Car0.0180.0000.0190.0000.0000.1040.0290.0370.4720.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0640.0000.0170.0720.0230.023
owner_Third Owner0.0000.0000.0000.0290.0000.0440.0550.1000.0760.0410.1800.0001.0000.0000.0000.0170.0000.0190.0150.0240.0000.0920.0050.0620.0500.2720.272
seats_100.0460.0000.0440.0100.0000.0450.0390.1110.0000.0000.0000.0000.0001.0000.0000.0000.1030.0000.0120.0000.0000.0050.0000.2850.0000.0360.036
seats_140.0000.0000.0000.0000.0000.0000.0000.0600.0000.0000.0000.0000.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.0000.000
seats_40.1160.0000.1140.0000.0000.7780.0530.2160.1320.0260.0280.0000.0170.0000.0001.0000.2470.0000.0470.0150.0000.0000.0000.1410.0000.3480.348
seats_50.3110.0340.3010.1150.0190.3480.2980.6000.2560.0000.0040.0000.0000.1030.0000.2471.0000.1740.7740.3560.2090.0380.0200.3470.0000.1090.109
seats_60.0100.0000.0050.0000.0000.0220.0000.1190.0000.0000.0000.0000.0190.0000.0000.0000.1741.0000.0310.0000.0000.0180.0000.0000.0210.0760.076
seats_70.3060.0240.2960.0890.0280.3270.2450.4370.3090.0130.0000.0000.0150.0120.0000.0470.7740.0311.0000.0710.0390.0000.0070.3710.0100.1320.132
seats_80.1140.0000.1110.0820.0000.1590.1000.2880.0250.0210.0140.0000.0240.0000.0000.0150.3560.0000.0711.0000.0080.0120.0000.0720.0040.0720.072
seats_90.0970.0000.0940.0000.0000.0480.0810.1880.0000.0000.0100.0000.0000.0000.0000.0000.2090.0000.0390.0081.0000.0260.0000.0480.0280.0450.045
seller_type_Individual0.0220.0000.0120.0220.0000.2120.0000.0580.1770.0500.1130.0640.0920.0050.0000.0000.0380.0180.0000.0120.0261.0000.1860.0870.2100.1500.150
seller_type_Trustmark Dealer0.0520.0000.0540.0000.0000.0480.0670.0000.0210.0000.0160.0000.0050.0000.0000.0000.0200.0000.0070.0000.0000.1861.0000.0000.0480.0410.041
torque0.4020.0000.3890.2430.2430.779-0.526-0.1620.5590.0000.0220.0170.0620.2850.0000.1410.3470.0000.3710.0720.0480.0870.0001.0000.3620.1020.102
transmission_Manual0.0060.0140.0190.0160.0000.5130.0510.2490.3480.0230.0470.0720.0500.0000.0000.0000.0000.0210.0100.0040.0280.2100.0480.3621.0000.1530.153
year0.2000.1160.198-0.570-0.5700.1660.0770.3460.5410.2220.2970.0230.2720.0360.0000.3480.1090.0760.1320.0720.0450.1500.0410.1020.1531.0001.000
year_squared0.2000.1160.198-0.570-0.5700.1660.0770.3460.5410.2220.2970.0230.2720.0360.0000.3480.1090.0760.1320.0720.0450.1500.0410.1020.1531.0001.000

Missing values

2025-12-04T04:02:11.300263image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-12-04T04:02:11.389602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

mileagemax_powertorquemax_torque_rpmnamefuel_Dieselfuel_LPGfuel_Petrolseller_type_Individualseller_type_Trustmark Dealertransmission_Manualowner_Fourth & Above Ownerowner_Second Ownerowner_Test Drive Carowner_Third Ownerseats_4seats_5seats_6seats_7seats_8seats_9seats_10seats_14yearkm_drivenyear_squaredkm_driven_squared
023.4074.00190.0002000.0586088.833333TrueFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse2014145500405619621170250000
121.14103.52250.0002500.0625000.000000TrueFalseFalseTrueFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse2014120000405619614400000000
223.0090.00219.7442750.0522960.091096TrueFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse2010127000404010016129000000
316.1088.20112.8154500.0170000.000000FalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse2007120000402804914400000000
420.1481.86113.7504000.0500000.000000FalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse20174500040682892025000000
517.3057.5076.5184500.0146250.000000FalseTrueFalseTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse2007175000402804930625000000
616.1037.0059.0002500.0522960.091096FalseFalseTrueTrueFalseTrueFalseTrueFalseFalseTrueFalseFalseFalseFalseFalseFalseFalse20015000400400125000000
723.5967.10170.0002400.0350000.000000TrueFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse20119000040441218100000000
820.0068.10160.0002000.0264285.571429TrueFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse2013169000405216928561000000
919.01108.45248.0002250.0471666.666667TrueFalseFalseTrueFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse20146800040561964624000000
mileagemax_powertorquemax_torque_rpmnamefuel_Dieselfuel_LPGfuel_Petrolseller_type_Individualseller_type_Trustmark Dealertransmission_Manualowner_Fourth & Above Ownerowner_Second Ownerowner_Test Drive Carowner_Third Ownerseats_4seats_5seats_6seats_7seats_8seats_9seats_10seats_14yearkm_drivenyear_squaredkm_driven_squared
583019.7046.3062.003000.0151554.527273FalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse20117300040441215329000000
583116.1037.0059.002500.068206.862069FalseFalseTrueTrueFalseTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalseFalse1997120000398800914400000000
583223.9567.1090.003500.0352666.666667FalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse20174500040682892025000000
583318.5082.85113.704000.0293749.916667FalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse2013250004052169625000000
583420.5167.0490.003500.0352000.000000FalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse20178000040682896400000000
583517.9262.1096.103000.0181809.476190FalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse2008191000403206436481000000
583618.9067.1090.003500.0271500.000000FalseFalseTrueTrueFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse20135000040521692500000000
583718.5082.85113.704000.0298749.916667FalseFalseTrueTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse2013110000405216912100000000
583816.80110.00235.442750.0236000.000000TrueFalseFalseTrueFalseTrueTrueFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse2007119000402804914161000000
583919.3073.90190.002000.0302272.727273TrueFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse2009120000403608114400000000

Duplicate rows

Most frequently occurring

mileagemax_powertorquemax_torque_rpmnamefuel_Dieselfuel_LPGfuel_Petrolseller_type_Individualseller_type_Trustmark Dealertransmission_Manualowner_Fourth & Above Ownerowner_Second Ownerowner_Test Drive Carowner_Third Ownerseats_4seats_5seats_6seats_7seats_8seats_9seats_10seats_14yearkm_drivenyear_squaredkm_driven_squared# duplicates
013.70138.10320.002700.0522960.091096TrueFalseFalseTrueFalseTrueFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalse201380000405216964000000002
117.70113.42144.154500.0522960.091096FalseFalseTrueFalseFalseTrueFalseFalseFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse201260000404814436000000002
219.3781.86160.003000.0522960.091096FalseFalseTrueTrueFalseTrueFalseFalseFalseTrueFalseTrueFalseFalseFalseFalseFalseFalse20031200004012009144000000002
319.3781.86160.003000.0522960.091096FalseFalseTrueTrueFalseTrueFalseTrueFalseFalseFalseTrueFalseFalseFalseFalseFalseFalse20041200004016016144000000002